Principal Manager- Software Development Engineer in Testing

About MontyCloud

MontyCloud recognized among the Top 10 Most Innovative Startups in cloud and AI-driven operations and help redefine Autonomous CloudOps for MSPs by building scalable, AI-powered solutions that optimize, operate, and monetize cloud environments at scale.

Job Overview

We are seeking an experienced and visionary Principal Manager Software Development Engineer in Testing to lead and scale quality engineering practices for our AI-driven cloud operations platform. This role is responsible for driving the organization-wide quality strategy, building high-performing teams, and ensuring the delivery of reliable, scalable, and high-quality products in a fast-paced SaaS environment. The ideal candidate combines technical depth, leadership excellence, and strategic thinking to establish quality engineering as a core competitive advantage.

Key Responsibilities

• Drive and evolve the organization-wide quality engineering strategy for our cloud-native SaaS platform
• Lead and standardize quality platforms, automation toolchains, and engineering best practices across teams in collaboration with platform and engineering groups
• Establish and govern quality gates, release processes, and reporting standards to ensure consistent delivery quality
• Define and track quality metrics and KPIs (e.g., defect leakage, coverage, release confidence) to drive continuous improvement
• Build, mentor, and scale high-performing quality engineering teams across multiple pods
• Drive hiring, org design, career development, and performance management for the QE function
• Lead the evolution of scalable automation frameworks and quality platforms across UI, API, and integration layers
• Define and implement test strategies for microservices-based and distributed systems
• Ensure effective integration of quality engineering within CI/CD pipelines with strong quality gates
• Drive API-first testing strategies, including contract and schema validation at scale
• Leverage observability (logs, metrics, traces) to enable production validation and improve system reliability (shift-right)
• Influence architecture and design decisions to improve testability, scalability, and overall system quality
• Partner with Engineering, Product, and Platform teams to embed quality practices early in the development lifecycle (shift-left)
• Support and evolve approaches for testing AI/ML-driven features, including validation of non-deterministic outputs
• Define and oversee performance and load testing strategies for distributed systems (k6, Locust, Gatling, etc.)
• Collaborate with SRE and infrastructure teams on test environments, tooling, and cloud-based execution
• Contribute to strategic planning and tooling decisions for quality engineering

Desired Skills and Requirements

Must Have

• 12-16 years of experience in quality engineering / test automation, with 5+ leadership experience
• Proven experience managing and scaling Quality Engineering teams (10+ members preferred)
• Experience leading modernization/migration initiatives (e.g., legacy to modern automation frameworks, tooling consolidation, platform upgrades)
• Strong programming background in Python, Java, or JavaScript
• Hands-on experience with modern test automation frameworks (Playwright/Cypress, Pytest or equivalent)
• Strong expertise in API testing and distributed systems validation
• Experience working with CI/CD pipelines and quality gates (Jenkins, GitHub Actions, GitLab CI)
• Solid understanding of cloud-native architectures (microservices, containers, distributed systems)
• Experience with Docker and Kubernetes-based environments
• Familiarity with cloud platforms (AWS preferred)
• Experience with contract testing / schema validation (OpenAPI, Pact)
• Working knowledge of observability tools (Prometheus, Grafana, ELK/OpenSearch)
• Experience with performance and load testing for distributed systems (k6, Locust, Gatling, etc.)
• Strong understanding of SDLC, Agile, and DevOps practices
• Familiarity with AI-driven or intelligent test automation tools

Good to Have

• Experience with AI/ML-driven systems or data-intensive platforms, including testing strategies
• Knowledge of event-driven architectures (Kafka, messaging systems)
• Exposure to security testing and compliance standards (OWASP, SOC2, etc…